Arbetsbeskrivning

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BackgroundThe increasing penetration of Battery Energy Storage Systems (BESS) has accelerated the transition toward sustainable transportation and resilient electrical grids. Modern BESS installations are evolving into modular systems composed of multiple battery systems and multiple parallel Power Conversion Systems (PCSs). Current hierarchical control architectures enable coordinated operation, it also introduces communication dependency, latency and scalability challenges. This type of architecture relies on hierarchical communication between the Energy Management System (EMS), local BESS controllers and individual PCS controllers. Multiple communication layers may introduce delays, synchronization errors and reduced dynamic performance in the grid-forming operation. Communication failures or packet loss can degrade power sharing, frequency regulation and transient stability.

The objective of this master thesis is to develop and validate an adaptive distributed control strategy for modular grid-forming Battery Energy Storage Systems comprising multiple parallel Power Conversion Systems (PCSs) and multiple Battery Energy Storage Systems (BESSs). The proposed solution should reduce communication dependency, improve dynamic performance during power dispatch, enhance robustness against communication failures and delays, and provide a scalable control architecture suitable for future large-scale energy storage systems.

Objectives

• Reduce dependency on hierarchical communication.
• Improve dynamic response during power dispatch.
• Maintain accurate active/reactive power sharing.
• Improve scalability for future modular BESS installations.
• Develop and evaluate virtual impedance control to reduce circulating currents caused by voltage, phase, and impedance mismatches among parallel PCSs.

• Conduct a literature review on grid-forming converters, Virtual Synchronous Generator (VSG) control, hierarchical and distributed control architectures for modular BESSs. Review the limitations of hierarchical communication, the motivation for adaptive control under varying operating conditions, and the applicability of Model Predictive Control (MPC) for predictive power sharing and constraint handling. Weeks 1-4]
• Develop a hierarchical grid-forming control model for multiple parallel PCSs and BESSs, including communication-based power dispatch, power-sharing control, and virtual impedance control. This model will serve as the reference for performance comparison. Weeks 5-12]
• Design and implement a distributed adaptive control strategy that reduces dependence on hierarchical communication while maintaining stable grid-forming operation, accurate active/reactive power sharing, and robust performance under communication delays and failures. If appropriate, investigate MPC to improve predictive power dispatch and constraint management. Weeks 13-21]
• Validate the proposed control strategy in MATLAB/Simulink, PLECS and/or PSCAD under representative operating scenarios, including load variations, communication delays, communication failures, and grid disturbances. Weeks 22-26]
• Compare the proposed distributed control with the baseline hierarchical controller using performance metrics including active/reactive power-sharing accuracy, frequency and voltage deviations, settling time, circulating current, communication bandwidth, and overall system robustness. Week 27-29]

• Two MS students with the solid backgrounds in electrical engineering, with basic knowledge of power electronics, control systems, and power systems
• Experience with MATLAB/Simulink or similar simulation tools like PSCAD or DIgSILENT is desirable.
• Knowledge or previous experience in grid-connected converter control, BESS/PCS systems, adaptive or distributed control, and power-system stability is considered a merit.

Are you excited to bring your skills and disruptive ideas to the table? We can’t wait to hear from you. Apply today!

Roeland BisschopHead of BESS Product [email protected]

Last application date: 2026-10-21

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